The project is proposed based on multimodal ultrasonic imaging omics building used for accurate prediction of the breast cancer and axillary lymph node metastasis load artificial intelligence forecasting model, this method can dig the hidden features of ultrasonic image is not visible to the naked eye, make up the subjectivity in the process of clinical doctors in diagnosis and treatment, provide accurate, objective basis for clinical decision making.
Study Type
OBSERVATIONAL
Enrollment
200
Preoperative conventional ultrasound (US), elastic ultrasound (UE) and contrast-enhanced ultrasound (CEUS) images were analyzed. Histopathological results were used as the gold standard. The cases were randomly divided into training set and test set with a ratio of 7:3. The US image, UE image and CEUS image of the maximum long-axis section of each lesion were selected, and the region of interest (ROI) of the lesion was manually delineated.
Accuracy of differential diagnosis between benign and malignant
ROC curve, sensitivity, specificity, accuracy, decision curve
Time frame: 2022.12.15-2023.12.30
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